The architecture of the Recurrent Neural Network (RNN) (Shown in Figure REF ) comprises loop connections, where the node activation of the next step depends on the previous step [1]}. Therefore, RNNs are capable of learning temporal sequences. RNN models process the spectral information of HSI data as time sequence considering the spectral bands as time steps [2]}. There are three basic models of RNN a) Vanilla, b) Long-Short-Term Memory (LSTM) and c) Gated Recurrent Unit (GRU).
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